One of the most critical and elusive resources of any financial institution is data. As organizations interact with customers in more digital ways, the mass of data grows. Integrating, accessing and managing data, with strong governance and controls, is a prerequisite for financial businesses today, both for compliance and ethical reasons.
But in many institutions, particularly for the established more traditional players, this data is frequently disparate, held across a range of platforms and systems. Because of this, firms struggle to generate value-adding insight from all the customer data held throughout the enterprise.
Connecting internal and external data has become significantly more top of mind in the midst of COVID-19. So much has changed so quickly. A bank’s customers are suddenly in very different financial positions compared to life pre COVID-19 and many factors are driving those changes, often faster than models can be adapted.
Connecting internal and external data is key in a post-COVID-19 mind-set
Inevitably, the adaptability of risk functions has become a key concern. How has the pandemic affected business segments or individual clients? What are the ramifications for each of the risk stripes? What exposures do we need to manage differently? How do we even know what is driving the changes?
In such times, leveraging data for insight moves from being a nice-to-have to an essential requirement. And with events moving so quickly, speed is of the essence.
The reality is that in our conversations with many clients over the past few frenetic months, the ability to access and harvest insights from internal and external (both structured and unstructured) data has become a pressing issue. The models and platforms used to gather data have come under stress in such a volatile, fluid and indeed unprecedented environment. Most likely, no internal model can be built fast enough to deal with the situations we are experiencing.
This is compounded by the fact that internal data really is only part of the story: it is essential to factor in external data too. Without reference to external data and emerging signals, how can any financial institution make truly robust decisions as the implications and knock-on effects of COVID-19 ripple through sectors and geographies?
Connecting internal and external data has become significantly more top of mind in the midst of COVID-19. So much has changed so quickly.
Harnessing the power of the cloud
It is in circumstances like this that the power of technology can help companies break new ground, bringing new capabilities into the enterprise. It is a time for firms to embrace data integration and analytics in the cloud. This is why at KPMG, our Financial Services Data Strategy team, together with experts from our Digital Lighthouse enablement teams, have been working with the major cloud providers to create solutions: flexible and scalable platforms that bring together cloud capabilities to help executives such as the Chief Risk Officer (CRO), Chief Financial Officer (CFO) or Chief Compliance Officer (CCO) harvest the power of their internal data and combine that with insights from external data to make faster and more informed business decisions.
KPMG solutions work via cloud platforms, where analytics tools can be turned toward data brought in from traditionally disconnected sources. The scale and speed of public cloud platforms allow firms to source and analyze a whole range of available information about a counterparty, including news reports, press releases, annual reports, 10k and other corporate filings, social sentiment and more. From this, and integrated with internal data, it builds a Decision Board presenting key information and options for execution and interaction.
By utilizing the cloud, new capabilities are opened up, such as access and proximity to third party data, the ability to process information at accelerated pace and increased scale, innovations around data analytics, data modelling and AI techniques. This creates a fuller picture, faster than any existing internal approach, with immediate integrations with workflow and execution tools.
Take credit risk as one example. As stresses hit the cruise industry, which has been significantly curtailed by the pandemic and faces an uncertain future, models and teams struggled to find external leading indicators and how the “ripple effect” would transcend single-counterparty views. Using a cloud-based approach to data management, it becomes possible to quickly assess the size of a lender’s direct exposure to cruise sector clients and also any related counterparties that supply services or goods to the cruise industry, such as catering, fuels, uniforms etc. It will present key information and relevant insights that can inform credit decision-making going forward. For an insurer, it could help actuaries assess the risks involved in providing coverage of different types and so factor that in to the setting of premiums. For an asset manager, it could help assess the value or prospects of companies in their funds. The applications are wide-ranging, for both front and back-office use cases
One of the strengths of converging data and analytics in the cloud is the access to smart and innovative analytics and intelligence tools. Commercial loans, for example, are often complex with bespoke wording and terms in contractual agreements. Traditional tools may struggle to recognize the relevant underlying data needed in source systems and loan documentation. But using the cloud and AI, an application can be taught to identify relevant data for making faster and more informed business decisions.
Credit risk is perhaps the most obvious use case for these cloud capabilities as we navigate the impact of the pandemic. But in fact, such applications can be applied to almost any need that relies on data-driven decision-making, such as operational risk issues, climate risk, macro-economic considerations, customer engagement and experience management, etc.
In this highly uncertain period, now is the time to harness the power of the cloud and advanced data analytics to assess the picture today and help predict and inform your actions in response to future needs for confident and immediate response to volatile market conditions.